Penetration Rate Research Articles

Terra-22: an Aerial Soil Sampling in Densely Compacted Agricultural Fields

Soil sampling is used in agriculture to monitor fields and plan fertilizer application. This task is typically performed manually, but ground robots have recently been introduced. However, ground robots are often slow and heavy, which contributes to soil compaction. Fast-flying drones could provide an interesting alternative to ground robots. However, drones are severely limited in their payload and in the forces that they can apply to the soil. This paper presents the Terra-22, the first airborne system capable of sampling densely compacted agricultural soils. To do so, many challenges were addressed, including the development of (i) a high-power density drilling system that outperforms typical brushed DC gear motor by 39%, (ii) a drill design that is 48% lighter than traditional steel auger drills and that keeps cross-contamination under 4%, and (iii) a drill penetration rate controller that reduces the torque requirement by 33% and the axial force requirement by eight folds when compared to a constant penetration speed controller. Outdoor soil sampling tests in a corn field (sandy loam soil, compaction between 0.8 MPa and 2 MPa) demonstrated a 94% success rate on flat terrain and a sampling duration under one minute.

Capacity Demand Analysis of Rural Biogas Power Generation System with Independent Operation Considering Source-Load Uncertainty

With the greatly increased penetration rate of wind power, photovoltaic, and other new energy sources in the power system, the proportion of controllable units gradually decreased, resulting in increased system uncertainty. The biogas power generation system can effectively alleviate the pressure caused by source-load uncertainty in such high-permeability systems of new energy sources such as wind power and photovoltaic. Hence, from the perspective of the power system, this paper introduces a capacity demand analysis method for a rural biogas power generation system capable of independent operation amidst source-load uncertainty. To enhance the depiction of pure load demand uncertainty, a scene set generation method is proposed, leveraging quantile regression analysis and Gaussian mixture model clustering. Each scene’s data and probability of occurrence elucidate the uncertainty of pure load demand. An integrated optimal operation model for new energy and biogas-generating units, free from energy storage capacity constraints, is established based on the generated scenario set. Addressing considerations such as biogas utilization rate and system operation cost, a biogas storage correction model, utilizing the gas storage deviation degree index and the cost growth rate index, is developed to determine biogas demand and capacity. The example results demonstrate the significant reduction in gas storage construction costs and charging and discharging imbalances achieved by the proposed model while ensuring systemic operational cost effectiveness.

Eco-Driving on Hilly Roads in a Mixed Traffic Environment: A Model Predictive Control Approach

Human driving behavior significantly affects vehicle fuel economy and emissions on hilly roads. This paper presents an ecological (eco) driving scheme (EDS) on hilly roads using nonlinear model predictive control (NMPC) in a mixed traffic environment. A nonlinear optimization problem with a relevant prediction horizon and a cost function is formulated using variables impacting the fuel economy of vehicles. The EDS minimizes vehicle fuel usage and emissions by generating the optimum velocity trajectory considering the longitudinal motion dynamics, the preceding vehicle’s state, and slope information from the digital road map. Furthermore, the immediate vehicle velocity and angle of the road slope are used to tune the cost function’s weight utilizing fuzzy inference methods for smooth maneuvering on slopes. Microscopic traffic simulations are used to show the effectiveness of the proposed EDS for different penetration rates on a real hilly road in Fukuoka City, Japan, in a mixed traffic environment with the conventional (human-based) driving scheme (CDS). The results show that the fuel consumption and emissions of vehicles are significantly reduced by the proposed NMPC-based EDS compared to the CDS for varying penetration rates. Additionally, the proposed EDS significantly increases the average speed of vehicles on the hilly road. The proposed scheme can be deployed as an advanced driver assistance system (ADAS).

Research Review on Multi-Port Energy Routers Adapted to Renewable Energy Access

With the continuous development of renewable energy technologies, both domestically and internationally, the focus of energy research has gradually shifted towards renewable energy directions such as distributed photovoltaics and wind power. The penetration rate of renewable energy generation is constantly increasing, at the same time, the elements in the grid are becoming increasingly complex, and large-scale energy storage, as well as a variety of electricity loads such as electric vehicle charging piles and data centers are gradually appearing. Therefore, traditional distribution methods of the power grid are difficult to ensure the stable operation of the power system and cannot achieve efficient integration of renewable energy. Consequently, some scholars have proposed the concept of an energy internet. Compared to traditional power grids, the energy internet employs more comprehensive power electronics and communication technologies, enabling the interconnection of various new and traditional energy sources, and effectively integrating renewable energy. As the core device in the energy internet, the energy router plays a role in energy transformation and distribution, facilitating multi-information interconnection and multi-energy exchange within the energy internet. At the level of distribution network, the energy router can realize the efficient access of various forms of energy and the flexible control and management, which is of great significance for the optimal operation of distribution network. Against this backdrop, this paper reviews the development and current research status of energy routers, systematically analyzes the typical topologies and related control technologies of multi-port energy routers and summarizes and forecasts key issues and future development trends, aiming to provide thoughts and reference for subsequent related research.

Understanding the foam stability mechanisms of complex formed by soy protein isolate and different charged polysaccharides: Air/water interfacial behavior and rheological characteristics

This study evaluated the foaming properties, the dynamic adsorption behavior at the air/water (A/W) interface and the foam rheological characteristics of complexes formed by soy protein isolate (SPI) and different charged polysaccharides, including chitosan (CS), guar gum (GUG) and gellan gum (GEG). The results showed that the SPI/CS10 had the highest initial foam volume (26.67 mL), which were 3.89 %, 100.08 % and 70.19 % higher than that of single SPI, SPI/GUG and SPI/GEG complexes, respectively. Moreover, three charged polysaccharides could all significantly improve the foam stability of complexes. Among them, foams stabilized by SPI/GEG10 were the most stable that the foam volume slightly changed (approximately 1 mL) and no drainage occurred throughout the whole recording process. The interfacial behavior analysis showed that SPI/CS10 had higher diffusion (Kdiff) and rearrangement rate (KR) but lower penetration rate (KP) at the A/W interface compared with single SPI, while SPI/GUG10 and all SPI/GEG complexes showed higher KR and KP but lower Kdiff. In addition, SPI/CS10 was beneficial to concurrently enhance the elastic strength and solid-like behavior of foam system, while all SPI/GEG complexes could improve the elastic strength of foam system but was not conducive to the solid-like behavior.

The role of information dissemination in sustaining a stable and Resilient Traffic Network under disruption

ABSTRACT A functioning roadway system is key to any society and economy. Traffic events such as maintenance and accidents reduce roadway capacity and can have immediate, large and lasting impact on traffic conditions. This paper investigates the role of information dissemination as a control tool for reducing the negative effects of a traffic event. It examines how timely information can prevent unnecessary route changes and counteract misinformation, restoring traffic equilibrium faster. Systems that recover equilibrium more rapidly are considered more resilient. A traffic flow evolution model is applied to analyze network behavior post-disruption, with a model parameter interpreted as an information dissemination penetration rate adjustable by operators. Numerical experiments investigate the effects of the penetration rate on travel times, revealing a critical rate for quickly re-establishing a new equilibrium. Beyond this rate, greater traffic oscillations can be expected. The study determines the best information penetration rate to maximize network resilience while ensuring stability.

Mathematical modeling of transdermal delivery of topical drug formulations in a dynamic microfluidic diffusion chamber in health and disease.

Mathematical models of epidermal and dermal transport are essential for optimization and development of products for percutaneous delivery both for local and systemic indication and for evaluation of dermal exposure to chemicals for assessing their toxicity. These models often help directly by providing information on the rate of drug penetration through the skin and thus on the dermal or systemic concentration of drugs which is the base of their pharmacological effect. The simulations are also helpful in analyzing experimental data, reducing the number of experiments and translating the in vitro investigations to an in-vivo setting. In this study skin penetration of topically administered caffeine cream was investigated in a skin-on-a-chip microfluidic diffusion chamber at room temperature and at 32°C. Also the transdermal penetration of caffeine in healthy and diseased conditions was compared in mouse skins from intact, psoriatic and allergic animals. In the last experimental setup dexamethasone, indomethacin, piroxicam and diclofenac were examined as a cream formulation for absorption across the dermal barrier. All the measured data were used for making mathematical simulation in a three-compartmental model. The calculated and measured results showed a good match, which findings indicate that our mathematical model might be applied for prediction of drug delivery through the skin under different circumstances and for various drugs in the novel, miniaturized diffusion chamber.

Indonesian Sundanese Local Wisdom as An Ethical Reference in Digital Media

Purpose: Cultural traditions as ancestral heritage contains local wisdom that can be utilized in community empowerment with communication technology to improve welfare.
  
 Methods: This research inventories the relevance of Sundanese cultural values to digital civilization. The type of research is qualitative research. The data collection techniques used are in-depth interviews, observation, and document analysis. 
  
 Results and Conclusion: The results of this study state that local wisdom can be explored scientifically from a cultural product, with in-depth interpretation. As a cultural product, cultural traditions contain various things related to the life and livelihood of the owner community, such as value systems, beliefs and religions, social norms, work ethics, and even the way social dynamics take place.
  
 Research implications: West Java Province, Indonesia occupies the highest positions reaching 16.4 million with an internet penetration rate of 36%. The majority of West Java people are Sundanese ethnic that have the noble values of cultural traditions and are used to regulate the Sundanese community order.
  
 Originality/value: It is significant for this local wisdom to be actualized again in the current era, and it is the basis for the view that everyone has ethical boundaries in seeing, hearing, and speaking, especially in verbal traditions.

Introduction of a modified QTBM model for predicting TBM penetration rate in rock, based on data from mechanized tunneling projects in Iran

Introduction of a modified QTBM model for predicting TBM penetration rate in rock, based on data from mechanized tunneling projects in Iran

An Optimized Grid‐Forming Control Strategy for the Flexible Interconnection System in Distribution Transformer Areas

The flexible interconnection system (FIS) in distribution transformer areas can improve the local consumption capacity of high penetration rate distributed photovoltaics and solve the problem of the high loading rate of distribution transformers. This paper presents an optimized grid‐forming control strategy for the FIS in distribution transformer areas. First, the DC side impedance small signal model of the FIS is built, and the reason for the stability difference of the FIS is analyzed when the active power flows in different directions. An optimized control structure is then presented based on the conventional grid‐forming control strategy. The theoretical analysis shows that the optimized grid‐forming control strategy can improve the stability of the FIS. Finally, the controller hardware‐in‐the‐loop experiments based on RT‐LAB confirm the effectiveness of the presented optimized control strategy. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

The effect of shear rate and overconsolidation ratios on undrained clay–suction caisson interface behaviors

The interface resistance during installation is crucial for the stability and safety of suction caisson in offshore geotechnical engineering, which is strongly affected by the penetration rate and soil–structure interface mechanical properties. This research conducts a series of clay–structure interface shear tests using modified direct simple shear device to fully study the mechanical behavior of clay–suction caisson interface. The effect of shear rate, over consolidation ratios (OCRs), interface boundary conditions, stress levels, and interface roughness were considered. Results show that as the OCR increases, the strength of both the clay and interface increase but show distinct patterns under constant volume (CV) and constant normal load (CNL) boundary condition. It was found that the interface strength is positively related to interface roughness and shear rate impact both the clay and corresponding interface strength. Under CNL conditions, the strength of normally consolidated (NC) clay decreases with rising shear rate, while the over consolidated (OC) clay demonstrate a opposite trend. In contrast, the effect of shear rate on interface behavior gets complicated owing to the combination of roughness, stress levels, and OCRs. Under CV conditions, the shear strength of clay and interface exhibits a logarithmic growth relationship with shear rates. The result of this work can provide a basis for interface resistance evaluation for suction caisson installation in clay.

The Impact of Indoor Air Humidity on the Infiltration of Ambient Particles

Ambient particles contribute to occupant exposure as they infiltrate indoor environments through building envelope cracks, impacting indoor air quality. This study investigates the impact of indoor air humidity on the infiltration of ambient particles, highlighting humidity’s crucial role in influencing particle dynamics in indoor environments. Employing a controlled chamber system, we conducted experiments to quantify the infiltration of size-resolved particles under varying relative humidity (RH) conditions. Both the total number and the mass concentration of particles increased with RH in the experimental chamber. The smallest particles (0.3–0.4 μm) experienced reduced infiltration at higher RH levels due to hygroscopic growth, while intermediate-sized particles showed increased infiltration, resulted from coagulation effects. Large particles (>1.0 μm) demonstrated reduced infiltration factors, caused by lower penetration and higher deposition rates, with minimal impact from RH changes. Our findings reveal that RH influences particle hygroscopic growth, deposition rate, and coagulation process, thereby affecting indoor particle size distribution and concentration.

Water shutoff treatment of low permeable reservoirs by in situ polymerization: laboratory scale development and verification through core flow experiments

Excessive water generation in oil reservoirs poses economic challenges, diminishing hydrocarbon yield and incurring additional costs for water management. This study focuses on enhancing reservoir conformance control, particularly in low-permeability zones with high water production, where traditional gel-based methods face limitations. The goal is improved penetration into narrow fractures and effective sealing of water-inflow zones through in situ polymerization and sequential cross-linking. The study systematically optimized key polymerization parameters, including initiator/monomer ratios, initiator types, and environmental conditions. Core flooding tests demonstrated a significant 17% increase in original oil recovery, alongside a substantial reduction in permeability. Analytical techniques such as CT scans, thin section scans, SEM, and EDS were employed to assess gel distribution within pores and penetration rates. This in situ polymerization and gelation approach show promise in addressing water production challenges, offering enhanced recovery, and adapting well to diverse reservoir conditions. The comprehensive optimization of polymerization parameters and the use of advanced analytical methods contribute to the study’s potential impact on mitigating economic and operational issues associated with excessive water production in oilfields.

Simulation study on basic road performance and modification mechanism of red mud modified asphalt mixture

Abstract In order to study the basic road performance and the mechanism of red mud modified asphalt, Marshall test, rut test, freeze-thaw splitting test, and immersion Marshall test were carried out for matrix asphalt mixture and red mud modified asphalt mixture, and molecular simulation technology was introduced to study the mechanism of red mud modified asphalt. The results showed that the penetration rate of red mud modified asphalt was lower than that of the matrix asphalt, and the softening point of asphalt was significantly improved after the addition of red mud, and the mixing of red mud reduced the asphalt ductility greatly. The intensity ratio (test strength ratio; TSR) of the freeze-thaw test of red mud modified asphalt under 3, 5, 7, 9, and 11% was increased by 13.18, 11.22, 13.54, 12.01, and 8.45%, respectively, compared with the matrix asphalt mixture, and the dynamic stability value increased by 127.23, 176.87, 200.99, 96.23, and 12.95%; the residual stability value of the immersion Marshall test increased obviously. Generally, the research of red mud modified asphalt is quite worthy, it can solve the problem of aluminum ore slag and reuse of resources, and provide a new way to extend the industrial chain.

Review of: "When the deposition rate is higher than the carbon penetration rate, carbon nanotubes are formed"

Review of: "When the deposition rate is higher than the carbon penetration rate, carbon nanotubes are formed"

Identifying Heterogeneous Willingness to Pay for New Energy Vehicles Attributes: A Discrete Choice Experiment in China

New energy vehicles (NEVs) have emerged as a promising solution to reduce carbon emissions and address environmental concerns in the transportation sector. In order to effectively accelerate market acceptance, it is crucial to prioritize the heterogeneity of consumer preferences for NEV attributes. This study employs the multinomial logit model (MNL) and latent class model (LCM) to investigate both observed and unobserved preference heterogeneity based on stated preferences obtained from a discrete choice experiment conducted across seven cities in China. Results from the MNL model indicate that all attributes significantly influence alternative utility. In particular, there are differences in the willingness to pay (WTP) for attributes of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs). Analysis of MNL subgroups reveals observed heterogeneity in WTP for identical attributes among consumers from regions with different latitudes and markets with different NEV penetration rates. Furthermore, the LCM model uncovers unobserved preference heterogeneity by classifying respondents into four distinct classes and identifies specific socioeconomic variables associated with each class. The recognition of heterogeneous WTP for NEV attributes across vehicle types, regions, markets, and consumer classes provides important implications for formulating targeted policies that promote the sustainable development of the NEV industry.

Deep Learning Method for Improving Rate of Penetration Prediction in Drilling

Summary The urgent global need to reduce CO2 emissions necessitates the development of sustainable power generation sources. Geothermal power emerges as a renewable and dependable energy option, harnessing the Earth’s natural heat sources for electricity generation. Unlike other renewables, geothermal energy offers uninterrupted power, immune to weather conditions. However, its efficiency hinges on technological innovation, particularly in the challenging realm of geothermal drilling. Rate of penetration (ROP) is a crucial drilling performance metric, and this study explores how deep learning models, particularly transformers, can optimize ROP prediction. Leveraging data from Utah Frontier Observatory for Research in Geothermal Energy (FORGE), we analyze the relationship between drilling parameters and ROP. Traditional drilling optimization methods face limitations, as drilling dysfunctions can disrupt the linear relationship between ROP and weight on bit (WOB). We propose a dynamic approach that allows adapting drilling parameters in real time to optimize ROP. Our experiments investigate optimal sampling intervals and forecast horizons for ROP prediction. We find that a 60-second sampling interval maximizes the transformer model’s forecasting accuracy. Additionally, we explore retraining to fine-tune models for specific wells, improving forecasting performance. Our transformer-based ROP forecaster outperforms deep learning models, achieving a low overall 5.22% symmetrical mean average percentage error (SMAPE) over a forecast horizon of 10 minutes. This model offers opportunities for cost-effective drilling optimization, with real-time accuracy, speed, and scalability. Future work will focus on larger data sets and integration with drilling automation systems to further enhance the model’s practicality and effectiveness in the field.

A New Workflow for Estimating Reservoir Properties With Gradient Boosting Model and Joint Inversion Using MWD Measurements

Triple-combo logs are important measurements for estimating geological, petrophysical, and geomechanical properties. Unfortunately, wireline and advanced logging-while-drilling (LWD) logs are typically dropped from the formation evaluation plan for unconventional wells due to economic constraints or borehole instability risks. Available measurements are typically measurement-while-drilling (MWD) gamma ray (GR) logs, along with surface measurements such as weight on bit (WOB), rate of penetration (ROP), torque, rotation per minute (RPM), and differential pressure. The development of a robust and rapid model for predicting reservoir properties using this limited data set would be of high value for geological evaluation. Estimating such properties is a challenging task due to the nonlinear relationship between the available log data and unknown reservoir properties. A novel workflow that combines two sequential models is presented. First is a machine-learning (ML) algorithm to predict triple-combo logs from drilling dynamics and GR logs. To train the ML algorithm, well logs obtained from multiple wells located in the Eagle Ford and Permian Basins are scrutinized to identify important features. This process includes depth shifting, outlier detection, and feature selection, which allows for strategic hyperparameter tuning. Several regression algorithms are investigated, and it is found that gradient boosting algorithms yield superior prediction performance. Unlike random forest methods, boosting algorithms train predictors sequentially, each trying to correct its predecessor. After triple-combo logs are predicted from MWD logs, a physics-based joint inversion model is applied to estimate various reservoir properties. The trained model is deployed on a blind test well, and the predicted logs show excellent agreement compared to the corresponding triple-combo measurements. The multimineral inversion using predicted triple-combo logs yields a geologic model that is validated with elemental capture spectroscopy (ECS) measurements. Additionally, reconstructed logs from the forward model closely match measured logs by minimizing the cost function. Therefore, real-time estimated geological, petrophysical, and geomechanical properties can reveal complex geologic information and be used to mitigate uncertainty related to drilling optimization, reservoir characterization, development planning, and reserve estimation. Using the MWD logs to predict triple-combo logs followed by a joint inversion is an innovative approach for geological evaluation with a limited data set. The developed workflow can successfully provide (1) geologic lithofacies identification and rock typing, (2) more confidence in real-time drilling operation, (3) reservoir properties prediction, (4) missing log imputations and pseudo-log generation with forward modeling, (5) guidance for future logging and perforation, (6) reference for seismic quantitative interpretation (QI) and well tie, and (7) potentially massive computation time saving from days to minutes.

Laser Drilling Through Hashma Sandstone

The application of laser in the drilling and perforation of oil wells can achieve great benefits such as reduced drilling costs and time with a higher rate of penetration (ROP) and elimination of casing necessity in oil and gas well drilling. This paper presents an original experimental investigation of Laser cutting through Hashma sandstone (a common quarry rock in Egypt) to develop a good understanding of the laser cutting process in sandstone. Five blocks of Hashma sandstone with dimensions of 35 cm × 35 cm × 10 cm were utilized to study the effects of the various parameters involved in the lasing (cutting) process in order to evaluate the cutting process through sandstone, investigate the effect of laser parameters on the process and the cutting mechanisms. The experimental results showed that the laser drilling can provide lower specific energy (SE) compared to conventional drilling methods, revealed the effect of various laser and rock parameters (such as beam power, intensity, duration, sample size, and orientation) on the cutting process, and demonstrated the laser cutting mechanisms through sandstone such as thermal spallation and melting mechanisms. Several parameters must be optimized for an optimum laser cutting process with the lowest SE, such as using the optimum beam power, beam duration (or Lasig time), and beam mode (continuous or pulsed). The optimum parameters may change from one case to another and depend on the overall interactions among the various variables such as thermal dissipation rate and purging system efficiency.

Investigation on the rock-breaking performance of specially-shaped PDC cutter under confining pressure conditions

Cutter shape has a significant influence on the rock-breaking performance of drill bit. Compared with conventional Polycrystalline Diamond Compact (PDC) cutter, the emergence of specially-shaped PDC cutters (SSPCs) with different geometric shapes is of great benefit to solve the problems of low rate of penetration (ROP) and rock-breaking efficiency in deep hard and hot dry rock formations. However, the high confining pressure and high in-situ stress (HCHS) have a significant influence on the rock-breaking performance of PDC cutter which cannot be ignored. Given that the above facts, this paper selects five kinds of PDC cutters with different cutter shapes, and implements a series of cutting experiments of granite under confining pressure conditions (CPCs) and atmospheric pressure condition (APC) using a true triaxial rock cutting device. The influence of cutter profile on the rock-breaking performance of PDC cutter was studied from the perspective of cutting force, mechanical specific energy (MSE), cuttings, coarseness index (CI) and fractal dimension. The results show that the rock breaking under CPC is more difficult than that under APC, resulting in the increased cutting force and MSE. Moreover, the cuttings obtained under CPC are smaller in size and the cutting grooves are smoother. Cutter shape has a great influence on the rock-breaking efficiency of PDC cutter, the rock-breaking efficiency of axe-shaped cutter is higher, while that of stinger cutter is lower. Moreover, PDC cutters with different shapes have different sensitivities to confining pressure, and stinger cutter has the lowest sensitivity to confining pressure, in other words, confining pressure has little influence on the rock breaking process of stinger cutter. What is more, the distribution of cuttings is characterized by the fractal dimension and particle size distribution parameter from the perspective of cuttings morphology and size respectively, and they present completely opposite changing trends. The obtained results are of great significance to the optimization of cutter profile, the design of bit cutter arrangement and the drilling of deep formation.